In addition to measuring the actual system energy consumption of a conventionally controlled SSAC and an LLCS with a radiant concrete floor, simulations were performed of other possible LLCS configurations that use SSAC or radiant ceiling panels (RCP). The goal of these simulations were to identify how much energy savings could be achieved by applying predictive pre-cooling control for low-lift chiller or air conditioner operation without the use of the concrete-core radiant floor system. The as-built LLCS configuration with concrete radiant floor cooling will here be referred to as an LLCS thermo-active building system (TABS).
Five different system configurations, described below, were simulated to assess and compare predictive control to achieve low-lift cooling using the TABS system, the split-system air conditioner (SSAC), and a radiant ceiling panel (RCP). These simulations were performed in the Matlab environment using the modeling methods described in chapters 2 and 3 and the control algorithm from chapter 4. The temperature response of the zone for all of these cases was modeled using the same temperature-CRTFs, which are the same as those used for the experimental assessment previously described in chapter 4. The system models for each case were different. Calibrated data-driven models of the LLCS chiller performance, developed for
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predictive control of the LLCS test chamber, were used for cases three through five. Un- calibrated data-driven models of the SSAC performance based on the data from chapter 3 were used for cases one and two, because calibration data was not collected for the SSAC. The five systems simulated are as follows:
1. Base case SSAC under thermostatic control (BASE-SSAC). The SSAC performance was modeled using the air conditioner performance described in chapter 3, but it was not calibrated to the as-built SSAC performance The SSAC studied in chapter 3 was the same make and model as that installed in the chamber, but not the same physical system. As a result, the actual performance of the SSAC in the test chamber differed from that of the curve-fit models from chapter 3. There is insufficient data to calibrate the SSAC model from chapter 3 to the as-built SSAC performance in the LLCS test chamber. Further data may be collected to calibrate the SSAC model, which would require more data on evaporator cooling rate, compressor speed and condenser fan speeds over a range of operating conditions. The zone air temperature setpoint for the thermostatic control was 23 Celsius, as in the experiments.
2. SSAC with predictive control (LLCS-SSAC). The SSAC performance was modeled as described above under BASE-SSAC. The same predictive pre-cooling control algorithm applied to the experimental LLCS-TABS system was used, as described in chapter 5.
3. TABS with predictive control (LLCS-TABS). The chiller system performance was modeled using the chiller performance map measured from the experimental test stand as described in chapter 3, but calibrated to the as-built performance of the chiller serving the concrete floor as described in chapter 6.
4. TABS with predictive control and a higher capacity radiant floor (LLCS-TABS+). This case was simulated to project the potential savings for an improved radiant concrete-core floor design, in which the floor had reduced pipe spacing, higher capacity, and less resistance between the bottom of the concrete and the chiller water loop. The temperature difference between the chilled water and the bottom of the concrete pavers was assumed to be half of that observed with the existing floor. Improvements to the thermal storage efficiency of the concrete floor, by adding insulation underneath, were not modeled. The chiller performance was modeled as described above under LLCS-TABS.
5. RCP with predictive control (LLCS-RCP). An RCP was modeled based on the radiant ceiling panel model described in [Armstrong et al 2009a]. The RCP total heat transfer coefficient was assumed to be 13.2 W/m2-K based on the results of [Causone et al 2009]. The entire test chamber ceiling, 3.65 m by 5.2 m, was assumed to be covered with RCP. The return water temperature was calculated using equation 20a in [Armstrong et al 2009a], which is a simple heat exchanger effectiveness-NTU relation between the zone air and the chilled water, using a single air temperature on the zone air side. The evaporating temperature was calculated based on the superheat control law implemented in the as-built system instead of with the flooded evaporator model described in [Armstrong et al 2009a]. The
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chiller performance was modeled as described above under LLCS-TABS, but using the return water temperature and subsequent evaporating temperature calculated for the RCP.
Each case was simulated under a typical summer week in Atlanta subject to standard efficiency internal loads. Forecasts of internal loads and outdoor temperature variations were perfect, because the forecasts rather than actual measured data from the experimental chamber were used for simulation. The total energy consumption over a typical summer week for each of these cases was calculated based on simulations of each system in Matlab. A summary of these findings is presented in Table 9.
Table 9 Energy consumption and relative savings from simulations of SSAC, TABS and RCP under with low-lift predictive pre-cooling control
BASE- SSAC LLCS- SSAC LLCS- TABS LLCS- TABS+ LLCS- RCP Cooling delivered (Wh) -47,940 -39,920 -53,200 -52,010 -39,420 Simulated energy (Wh) 11,110 8,038 11,072 10,824 5,285
Measured energy (Wh) 14,053 n/a 10,982 n/a n/a
Error in simulation 20.9% n/a -0.8% n/a n/a
Savings relative to
simulated base case base 27.6% base 2.2% 52.3%
The first important point about the results shown in Table 9 is that the simulated SSAC does not accurately model the as-built SSAC. There is a 20.9 percent difference between the measured SSAC system performance and the simulated SSAC system performance. This difference may have the following causes. First, the actual transient performance of the SSAC is not reflected in its steady-state performance map from chapter 3, which is the model used to simulate SSAC performance. Second, it is likely that the performance of the as-built SSAC is different from the SSAC tested in chapter 3, just as the as-built chiller performance was different from the performance map from chapter 3 and required the calibrations described in section 6.1.1. Currently, not enough information is available to calibrate the performance map model of the SSAC to its as-built performance. The same model structure should be applicable to the as-built SSAC, but the coefficients of the model may be somewhat different than the SSAC tested in chapter 3.
With these differences in system modeling in mind, the results of the simulations have only been compared when the same underlying cooling system model has been used for both cases. Thus, it is reasonable to compare the BASE-SSAC case to the LLCS-SSAC case because the exact same models were used for both simulations, only the control laws were changed. The same is true for the LLCS-TABS, LLCS-TABS+, and LLCS-RCP cases to the extent that the TABS+ and RCP assumptions are achievable and representative of a real system. The same calibrated chiller performance was used for those three cases.
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The following conclusions can be drawn from the results in Table 9. First, by employing predictive pre-cooling control directly to the SSAC, simulations suggest over 27 percent energy savings relative to conventional control. These savings are comparable to the measured energy savings of the LLCS-TABS relative to the SSAC. However, it should not be taken at face value that an LLCS-SSAC could save the same energy as an LLCS-TABS in any situation. The ability of the SSAC to achieve the same savings as the TABS under predictive control for the modeled LLCS test chamber may be the result, in part, of low internal load densities relative to the chiller capacity. This mismatch results in less need for storing cooling energy in the concrete, and the SSAC can provide enough pre-cooling despite the fact that it is less effective than the TABS system at pre-cooling the concrete slab. It may also be affected by the thermal storage capacity of the slab, which is reduced by losses to below from the concrete-floor of the LLCS test chamber. This is evident in the amount of total cooling delivered by each case. The TABS systems provide far more cooling than required to meet the load due to losses from the floor. The cooling delivered by the TABS system in simulation is roughly 25 percent more than that of the RCP. This agrees, approximately with the results of a physical model of the concrete floor, which shows that the losses from the bottom of the floor may range from 15 to 30 percent depending on the actual thermal conductivity of the concrete, as described in Appendix B.1. Second, improving the TABS system, represented by the LLCS-TABS+ case, to achieve higher chilled water temperatures may not achieve significantly greater savings than the LLCS-TABS case. Only an additional 2.2 percent savings was simulated for the LLCS-TABS+. This is likely because the chilled water temperatures and evaporating temperatures are only a few degrees warmer in the LLCS-TABS+ case than in the LLCS-TABS case.
Lastly, the LLCS-RCP system shows significant potential for energy savings over the LLCS-TABS case for the existing test chamber, with over 50 percent simulated savings relative to LLCS- TABS. This is primarily the result of significantly higher chilled water temperatures. However, again, the LLCS-RCP savings are skewed because of the mismatch between the chiller capacity and the internal loads, as well as the low thermal storage efficiency of the LLCS test chamber. Better matching of capacity and load and improved concrete-core thermal storage efficiency should result in more savings from the LLCS-TABS relative to the LLCS-RCP. In the LLCS-RCP simulated case, the RCP system runs primarily during occupied hours because it can efficiently meet the loads with higher chilled water temperatures without utilizing passive TES overnight. In summary, the simulations show that predictive pre-cooling control for low-lift chiller or air conditioner operation has great potential for energy savings even without a TABS concrete radiant floor cooling system. Simply applying predictive pre-cooling control to the conventional SSAC resulted in 27 percent simulated energy savings. More research is needed to confirm and evaluate the actual energy savings achievable for each of these configurations and many other LLCS configurations beyond TABS, SSAC, or RCPs.
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